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arXiv 2022年

作者： Yang, Guang Chen, Xingguo Yang, Shangdong Wang, Huihui Dong, Shaokang Gao, Yang The the Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications National Engineering Laboratory for Agri-Product Quality Traceability Beijing Technology and Business University China The State Key Laboratory for Novel Software Technology Nanjing University China The PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology China

With rising uncertainty in the real world, online Reinforcement Learning (RL) has been receiving increasing attention due to its fast learning capability and improving data efficiency. However, online RL often suffers from complex Value Function Approximation (VFA) and catastrophic interference, creating difficulty for the deep neural network to be applied to an online RL algorithm in a fully online setting. Therefore, a simpler and more adaptive approach is introduced to evaluate value function with the kernel-based model. Sparse representations are superior at handling interference, indicating that competitive sparse representations should be learnable, non-prior, non-truncated and explicit when compared with current sparse representation methods. Moreover, in learning sparse representations, attention mechanisms are utilized to represent the degree of sparsification, and a smooth attentive function is introduced into the kernel-based VFA. In this paper, we propose an Online Attentive Kernel-Based Temporal Difference (OAKTD) algorithm using two-timescale optimization and provide convergence analysis of our proposed algorithm. Experimental evaluations showed that OAKTD outperformed several Online Kernel-based Temporal Difference (OKTD) learning algorithms in addition to the Temporal Difference (TD) learning algorithm with Tile Coding on public Mountain Car, Acrobot, CartPole and Puddle World tasks. Copyright © 2022, The Authors. All rights reserved.

关键词： Learning algorithms

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The Algorithms of Predicting Bacterial Essential Genes and NcRNAs by Machine Learning

The Algorithms of Predicting Bacterial Essential Genes and N...

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作者： Yuannong Ye Dingfa Liang Zhu Zeng Bioinformatics and Biomedical Big Data Mining Laboratory Department of Medical Informatics School of Big Health Guizhou Medical University Cells and Antibody Engineering Research Center of Guizhou Province Key Laboratory of Biology and Medical Engineering School of Biology and EngineeringGuizhou Medical University Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education Guizhou Medical University

Essential genes are indispensable for biological survival. Thus it is of great significance to identify and study essential genes. A machine learning method, K-Nearest Neighbor, is used for development of predicting essential bacterial genes. The homologous features, including sequence homology and functional homology, of the bacterial genomes are extracted for determining essential genes. Based on the features, we use K-Nearest Neighbor algorithm for determining of gene function. And we tune the minimum matching parameter(K) in the essential gene predicted model for building an optimal model of the Escherichia coli specificity model. The corresponding optimal parameter(K) is then extended to other bacterial essential genes predicting models. After cross validation, the highest accuracy is 0.89 while K between 5 and 7. Therefore, the features we extracted can increase the accuracy of the bacterial essential gene prediction. In the premise, we found that the prediction accuracy of the prediction model based on K-Nearest Neighbor was not significantly different in different evolutionary distances between organisms in the database and the investigated species. That means the machine learning model can be extended to more distant species. It wills have a better predictive performance for predicting essential genes of distant species than the usual sequence-based methods.

关键词： Essential genes Machine learning KNN

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Integrated Helicobacter Pylori Genome database and Its Analysis

Integrated Helicobacter Pylori Genome Database and Its Analy...

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作者： Liufeng Zheng Mujuan Guo Dingfa Liang Yuannong Ye Cells and Antibody Engineering Research Center of Guizhou Province Key Laboratory of Biology and Medical Engineering School of Biology and EngineeringGuizhou Medical University Bioinformatics and Biomedical Big Data Mining Laboratory Department of Medical Informatics School of Big Health Guizhou Medical University Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education Guizhou Medical University

The shape of helicobacter pylori(HP) is usually helical or S-shaped,which makes it to have the feature of highly divergent. Besides, its distribution also is different greatly in space and time, which is the factor to lead to multiple infection. In addition, in the same infected person, multiple infection also appeared in different regions of strain gene infection origin. Therefore, it is of great significance to study the genomic diversity and evolutionary analysis of Helicobacter pylori. In this paper, we are to analyze the homology of multiple sequences using Clustal X1.83 and meanwhile to construct the homologous genome evolutionary tree by MEGA7.0 to analyze the its function. The purpose of this study is to compare the genomic evolutionary differences of Helicobacter pylori among populations in different regions, and to discuss the significance of its infection prevalence and genomic variation in geographical changes, so as to conduct further discussion on the molecular level research mechanism of Helicobacter pylori.

关键词： Helicobacter pylori ClustalX MEGA Genome Phylogenetic tree

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Optimization of Gene Translation Using SD Complementary Sequences and Double Codons

Optimization of Gene Translation Using SD Complementary Sequ...

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作者： Dingfa Liang Zhumian Huang Liufeng Zheng Yuannong Ye Cells and Antibody Engineering Research Center of Guizhou Province Key Laboratory of Biology and Medical Engineering School of Biology and EngineeringGuizhou Medical University Bioinformatics and Biomedical Big Data Mining Laboratory Department of Medical Informatics School of Big Health Guizhou Medical University Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education Guizhou Medical University

Studies have confirmed that the growth, development and maintenance structure and function of all living organisms are determined by their genes, but the speed of gene translation products is affected by various internal and external factors. Therefore, studying the gene translation speed is extremely important for production and improving the speed through a variety of ways has always been an important subject. In recent years, the found of codon usage bias, t RNA recycling model and SD sequence-like structure provide another way to optimize the translation efficiency. These methods are almost based on codon usage theory to optimize gene sequence to speed up or slow down the translation speed so as to regulate the cell expression and metabolism. This paper is combined the three theories above, aimed at *** to design some reasonable algorithm to optimize gene sequence and thus using codon adaptation index(CAI) to evaluate the optimized effect.

关键词： E.coli Optimization of gene translation efficiency Codon usage bias tRNA-recyling model SD sequence-like structure

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MFCLIP: Multi-modal Fine-grained CLIP for Generalizable Diffusion Face Forgery Detection

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IEEE Transactions on Information Forensics and Security 2025年 20卷 5888-5903页

作者： Zhang, Yaning Wang, Tianyi Yu, Zitong Gao, Zan Shen, Linlin Chen, Shengyong Qilu University of Technology Shandong Academy of Sciences Faculty of Computer Science and Technology Jinan 250014 China National University of Singapore School of Computing 21 Lower Kent Ridge Rd 119077 Singapore Great Bay University School of Computing and Information Technology Dongguan 523000 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen 518060 China Qilu University of Technology (Shandong Academy of Sciences) Shandong Artificial Intelligence Institute Jinan 250014 China Tianjin University of Technology Key Laboratory of Computer Vision and System Ministry of Education Tianjin 300384 China Shenzhen University Computer Vision Institute College of Computer Science and Software Engineering Shenzhen 518060 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518129 China Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen 518060 China

The rapid development of photo-realistic face generation methods has raised significant concerns in society and academia, highlighting the urgent need for robust and generalizable face forgery detection (FFD) techniques. Although existing approaches mainly capture face forgery patterns using image modality, other modalities like fine-grained noises and texts are not fully explored, which limits the generalization capability of the model. In addition, most FFD methods tend to identify facial images generated by GAN, but struggle to detect unseen diffusion-synthesized ones. To address the limitations, we aim to leverage the cutting-edge foundation model, contrastive language-image pre-training (CLIP), to achieve generalizable diffusion face forgery detection (DFFD). In this paper, we propose a novel multi-modal fine-grained CLIP (MFCLIP) model, which mines comprehensive and fine-grained forgery traces across image-noise modalities via language-guided face forgery representation learning, to facilitate the advancement of DFFD. Specifically, we devise a fine-grained language encoder (FLE) that extracts fine global language features from hierarchical text prompts. We design a multi-modal vision encoder (MVE) to capture global image forgery embeddings as well as fine-grained noise forgery patterns extracted from the richest patch, and integrate them to mine general visual forgery traces. Moreover, we build an innovative plug-and-play sample pair attention (SPA) method to emphasize relevant negative pairs and suppress irrelevant ones, allowing cross-modality sample pairs to conduct more flexible alignment. Extensive experiments and visualizations show that our model outperforms the state of the arts on different settings like cross-generator, cross-forgery, and cross-dataset evaluations. © 2005-2012 IEEE.

关键词： CLIP Diffusion face forgery detection Image-noise fusion Sample pair attention Transformer

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Analysis of Risk Factors for Hemorrhagic Complications in Pediatric Acute Liver Failure 10th

Analysis of Risk Factors for Hemorrhagic Complications in Pe...

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10th China Health Information Processing Conference, CHIP 2024

作者： Xiong, Qiang Xiao, Li Wang, Ruijue Li, Wenlong Hu, Songhua Hu, Qinshi Wang, Zhuangcheng Xu, Ximing Department of Hepatobiliary Surgery Children’s Hospital of Chongqing Medical University National Clinical Research Center for Child Health and Disorders Ministry of Education Key Laboratory of Child Development and Disorders Chongqing Key Laboratory of Pediatrics Chongqing China Big Data Engineering Center Children’s Hospital of Chongqing Medical University National Clinical Research Center for Child Health and Disorders Ministry of Education Key Laboratory of Child Development and Disorders Chongqing China Department of Pediatric Surgery Yibin Hospital Affiliated to Children’s Hospital of Chongqing Medical University Chongqing China Department of Epidemiology and Health Statistics School of Public Health Chongqing Medical University Yixue Road Chongqing400016 China Department of Epidemiology and Health Statistics School of Public Health Wannan Medical College Wuhu China

ISBN: (纸本)9789819637515

Objective: To analyze the clinical data of children with acute liver failure to identify risk factors for hemorrhagic complications, thereby providing a basis for clinical diagnosis and treatment decisions in pediatric acute liver failure (PALF). Methods: Clinical data from children diagnosed with acute liver failure and hospitalized at the Children’s Hospital affiliated with Chongqing Medical University from January 2014 to June 2024 were collected. data included general information, laboratory indicators, and hemorrhagic complications. Patients were categorized into hemorrhagic and non-hemorrhagic complication groups for comparative analysis. Results: A total of 663 cases were analyzed, with 239 cases (36.05%) having hemorrhagic complications and 424 cases (63.95%) without. Only 21 cases (3.17%) had spontaneous bleeding. Multivariate analysis identified infection (OR = 4.05, 95%CI: 2.47~6.64, p <0.001), hepatorenal syndrome (HRS) (OR = 2.95, 95%CI: 1.82~4.77, p <0.001), multiple organ dysfunction syndrome (MODS) (OR = 2.47, 95%CI: 1.57~3.88, p <0.001), low platelet count (≤50 × 10^9/L) (OR = 2.51, 95%CI: 1.58~3.99, p <0.001), and low fibrinogen (≤1 mg/dL) (OR = 1.73, 95%CI: 1.12~2.69, p = 0.014) as independent risk factors for hemorrhagic complications in children with acute liver failure. Conclusion: Spontaneous bleeding in PALF is relatively rare, with infection, HRS, MODS, thrombocytopenia, and hypofibrinogenemia being high-risk factors for bleeding. Active prevention and control of infections and maintenance of organ function are crucial in preventing bleeding in PALF. Routine coagulation tests like prothrombin time and international normalized ratio are not sufficient to predict bleeding risk in PALF, necessitating a more comprehensive coagulation evaluation system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Diagnosis

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Max-Min Fairness in IRS-Aided MISO Broadcast Channel via Joint Transmit and Reflective Beamforming

Max-Min Fairness in IRS-Aided MISO Broadcast Channel via Joi...

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GLOBECOM 2020 - 2020 IEEE Global Communications Conference

作者： Caihong Kai Wenqi Ding Wei Huang Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) School of Computer Science and Information Engineering Hefei University of Technology Ministry of Education Hefei China

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

The potential application of intelligent reflecting surfaces (IRSs) for future wireless cellular communication systems has motivated the study of metasurface for achieving additional space degree of freedom, where IRS is used to enhance the desired signal strength and suppress the interference. In this paper, by using the additional design degree of freedom provided by the IRS, we jointly optimize the transmit beamforming vector at the BS and the reflective beamforming vector at the IRS to maximize the minimum rate in the IRS-aided multi-user multiple-input-single-output broadcast channel (MISO-BC), subject to the unit modulus constraints of the reflective beamforming vector. In order to solve the non-convex optimization problem, we propose an efficient algorithm based on alternating optimization. In particular, we optimize the transmit beamforming vectors via the second-order cone problem (SOCP) and reflective beamforming vector by using the semi-definite relaxation (SDR). Numerical results show that the use of IRS leads to significant higher SINR values than benchmark schemes without IRS.

关键词： Wireless communication Array signal processing Transmitters Interference MISO communication Optimization Signal to noise ratio

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Adaptive domain of dynamic distribution based on manifold space

Adaptive domain of dynamic distribution based on manifold sp...

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IEEE International Conference on big knowledge (ICBK)

作者： Daoyuan Yu Xuegang Hu Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology Hefei China

ISBN: (数字)9781728181561

ISBN: (纸本)9781728181578

Domain adaption aims to use the source domain knowledge to assist the model learning. Most of the existing methods are based on the feature representation learning model, which are achieved by aligning the data distribution between two domains. However, in the process of feature representation learning, due to the diversity of distribution differences between domains, it faces the problems of degenerated feature transformation and unevaluated distribution alignment, which bring challenges to the existing research. Therefore, the dynamic distribution alignment factors of marginal distribution and conditional distribution are introduced to reduce the spatial distortion in the process of feature representation, and the domain adaptation is realized based on the dynamic manifold regularization constraints and structural risk minimization learning. In this paper, we propose the structural risk minimization and an improved dynamic manifold regularization constraint to solve these problems. Experimental results show that compared with traditional methods and deep level methods, the algorithm in this paper has a significant improvement in classification accuracy.

关键词： Manifolds Feature extraction Task analysis Distortion Adaptation models Risk management Kernel

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Hexagonally ordered microbowl arrays decorated with ultrathin CuInS_(2) nanosheets for enhanced photoelectrochemical performance

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Journal of Energy Chemistry 2020年第12期29卷 134-142页

作者： Ming Li Le Chen Yanjie Su Huan Yin Kexiang Hu State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyKey Laboratory of Optoelectronic Information Processing of Guangxi Colleges and Uniy/ersitiesGuilin 541004GuangxiChina Key Laboratory for Thin Film and Microfabrication of the Ministry of Education Department of Micro/Nano ElectronicsSchool of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China National and Local Joint Engineering Laboratory of Internet Technology on Mine School of Information and Control EngineeringChina University of Mining and TechnologyXuzhou 221008JiangsuChina School of Physics and Telecommunication Engineering Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data ProcessingYulin Normal UniversityYulin 537400GuangxiChina

This paper demonstrates the design and fabrication of three-dimensional(3 D) hexagonally ordered microbowl arrays(MBAs) decorated with Cu In S2 nanosheets for enhanced photoelectrochemical(PEC) performance. The 3 D MBAs are fabricated by a micro-fabrication technique. The ultrathin CuInS2 nanosheets are grown on the 3 D electrodes by solvothermal transformation of Cu film. The photocurrent density of 3 D photocathode(CuInS2@MBAs) is about two times higher than that of the planar counterpart(CuInS2@Planar). The improved PEC performance can be ascribed to the elevated light trapping ability and the increased surface area for loading photocatalysts. In addition, CdS quantum dots as cocatalysts are modified onto the Cu In S2 nanosheets to further enhance the PEC activity because the formed p-n heterojunction can accelerate the separation of photogenerated carriers. As a result, the 3 D photocathode of CuInS2/CdS@MBAs shows an optimal incident photon to current efficiency of 10% at the wavelength of400 nm. It is believed that this work can be generalized to design other hierarchical 3 D photoelectrodes for improved solar water splitting.

关键词： Microbowl array CuInS_(2) Nanosheet Photocathode Photoelectrochemical performance

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Roof greening in major Chinese cities possibly afford a large potential carbon sink

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Science Bulletin 2024年第20期69卷 3216-3220页

作者： Chao Yang Yinghui Zhang Min Chen Song Zhu Yuzhi Tang Zhixin Zhang Wei Ma Huizeng Liu Junyi Chen Bohui Tang Dejin Zhang Zhengdong Huang Xuqing Wang Wei Tu Cuiling Liu Tiezhu Shi Haiying Xu Aihong Cui Fanyi Meng Tianhong Zhao Kai Guo Wenhao Guo Bi Fan Quande Qin Wuyang Hong Haishan Wu Bing Wang Jinrong Zeng Ka Wai Wu Qingquan Li Key Laboratory for Geo-Environmental Monitoring of Great Bay Area Ministry of Natural Resources&Guangdong Key Laboratory of Urban InformaticsShenzhen UniversityShenzhen 518060China School of Architecture and Urban Planning Shenzhen UniversityShenzhen 518060China Key Laboratory of Virtual Geographic Environment Ministry of EducationNanjing Normal UniversityNanjing 210023China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Shenzhen Zhiyuan Space Innovation Technology Co. LtdShenzhen 518060China Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen 518107China School of Geography and Ocean Science Nanjing UniversityNanjing 210008China School of Geography Nanjing Normal UniversityNanjing 210023China School of Civil Engineering Chongqing Jiaotong UniversityChongqing 400074China Institute for Advanced Study&Shenzhen University Shenzhen 518060China Tiandu-Shenzhen University Deep Space Joint Laboratory Shenzhen UniversityShenzhen 518060China Faculty of Land Resource Engineering Kunming University of Science and TechnologyKunming 650093China Center for Hydrogeology and Environmental Geology China Geological SurveyBaoding 071051China Department of Landscape Architecture and Urban Planning Texas A&M UniversityTX 77840USA Department of Geography Hong Kong Baptist UniversityHong Kong 999077China College of Civil and Transportation Engineering Shenzhen UniversityShenzhen 518060China College of Big Data and Internet Shenzhen Technology UniversityShenzhen 518118China Faculty of Geosciences and Environmental Engineering Southwest Jiaotong UniversityChengdu 611756China College of Management Shenzhen UniversityShenzhen 518060China WeBank(Shenzhen)Co. LtdShenzhen 518060China Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong Kong 100872China Esri C

China is experiencing accelerated urbanisation,with a large number of people moving from rural to urban areas[1].It has resulted in large losses in the net primary production(NPP),biodiversity and carbon stocks and an increase in environmental pollution and CO_(2)emissions[2–4].In 2015,196 countries signed the Paris Agreement and committed to setting long-term goals to jointly manage climate change and reduce their individual emissions,aiming to control the increase in global average temperature from the pre-industrial level to below 2℃and to curtail the temperature rise within 1.5℃till the end of the 21st century[5].China is bolstering its efforts to achieve the climate change mitigation goals and has announced a plan for achieving carbon neutrality by 2060[6].The carbon neutrality goal poses a challenge to the current policies promoting rapid urbanisation across China.

关键词： jointly carbon goals

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